From 9601ae9aa6341655d71ca55f5dc038edfc5e3b02 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B8=AD=E9=98=B3=E9=98=B3?= Date: Wed, 14 Jan 2026 15:52:27 +0800 Subject: [PATCH 1/7] feat: add in mem-reader --- src/memos/api/handlers/component_init.py | 3 +- src/memos/mem_feedback/feedback.py | 3 +- src/memos/mem_reader/base.py | 23 ++++++++++++- src/memos/mem_reader/factory.py | 32 +++++++++++++++++-- src/memos/mem_reader/simple_struct.py | 3 ++ .../init_components_for_scheduler.py | 3 +- 6 files changed, 60 insertions(+), 7 deletions(-) diff --git a/src/memos/api/handlers/component_init.py b/src/memos/api/handlers/component_init.py index 56f8ac195..76af6decf 100644 --- a/src/memos/api/handlers/component_init.py +++ b/src/memos/api/handlers/component_init.py @@ -183,7 +183,8 @@ def init_server() -> dict[str, Any]: else None ) embedder = EmbedderFactory.from_config(embedder_config) - mem_reader = MemReaderFactory.from_config(mem_reader_config) + # Pass graph_db to mem_reader for recall operations (deduplication, conflict detection) + mem_reader = MemReaderFactory.from_config(mem_reader_config, graph_db=graph_db) reranker = RerankerFactory.from_config(reranker_config) feedback_reranker = RerankerFactory.from_config(feedback_reranker_config) internet_retriever = InternetRetrieverFactory.from_config( diff --git a/src/memos/mem_feedback/feedback.py b/src/memos/mem_feedback/feedback.py index 15d7c336a..1d199c6cb 100644 --- a/src/memos/mem_feedback/feedback.py +++ b/src/memos/mem_feedback/feedback.py @@ -76,7 +76,8 @@ def __init__(self, config: MemFeedbackConfig): self.llm: OpenAILLM | OllamaLLM | AzureLLM = LLMFactory.from_config(config.extractor_llm) self.embedder: OllamaEmbedder = EmbedderFactory.from_config(config.embedder) self.graph_store: PolarDBGraphDB = GraphStoreFactory.from_config(config.graph_db) - self.mem_reader = MemReaderFactory.from_config(config.mem_reader) + # Pass graph_store to mem_reader for recall operations (deduplication, conflict detection) + self.mem_reader = MemReaderFactory.from_config(config.mem_reader, graph_db=self.graph_store) self.is_reorganize = config.reorganize self.memory_manager: MemoryManager = MemoryManager( diff --git a/src/memos/mem_reader/base.py b/src/memos/mem_reader/base.py index 391270bcf..b34abf9a1 100644 --- a/src/memos/mem_reader/base.py +++ b/src/memos/mem_reader/base.py @@ -1,17 +1,38 @@ from abc import ABC, abstractmethod -from typing import Any +from typing import TYPE_CHECKING, Any from memos.configs.mem_reader import BaseMemReaderConfig from memos.memories.textual.item import TextualMemoryItem +if TYPE_CHECKING: + from memos.graph_dbs.base import BaseGraphDB + + class BaseMemReader(ABC): """MemReader interface class for reading information.""" + # Optional graph database for recall operations (for deduplication, conflict + # detection .etc) + graph_db: "BaseGraphDB | None" = None + @abstractmethod def __init__(self, config: BaseMemReaderConfig): """Initialize the MemReader with the given configuration.""" + def set_graph_db(self, graph_db: "BaseGraphDB | None") -> None: + """ + Set the graph database instance for recall operations. + + This enables the mem-reader to perform: + - Semantic deduplication: avoid storing duplicate memories + - Conflict detection: detect contradictions with existing memories + + Args: + graph_db: The graph database instance, or None to disable recall operations. + """ + self.graph_db = graph_db + @abstractmethod def get_memory( self, scene_data: list, type: str, info: dict[str, Any], mode: str = "fast" diff --git a/src/memos/mem_reader/factory.py b/src/memos/mem_reader/factory.py index ff24e5c77..2749327bf 100644 --- a/src/memos/mem_reader/factory.py +++ b/src/memos/mem_reader/factory.py @@ -1,4 +1,4 @@ -from typing import Any, ClassVar +from typing import TYPE_CHECKING, Any, ClassVar, Optional from memos.configs.mem_reader import MemReaderConfigFactory from memos.mem_reader.base import BaseMemReader @@ -8,6 +8,10 @@ from memos.memos_tools.singleton import singleton_factory +if TYPE_CHECKING: + from memos.graph_dbs.base import BaseGraphDB + + class MemReaderFactory(BaseMemReader): """Factory class for creating MemReader instances.""" @@ -19,9 +23,31 @@ class MemReaderFactory(BaseMemReader): @classmethod @singleton_factory() - def from_config(cls, config_factory: MemReaderConfigFactory) -> BaseMemReader: + def from_config( + cls, + config_factory: MemReaderConfigFactory, + graph_db: Optional["BaseGraphDB | None"] = None, + ) -> BaseMemReader: + """ + Create a MemReader instance from configuration. + + Args: + config_factory: Configuration factory for the MemReader. + graph_db: Optional graph database instance for recall operations + (deduplication, conflict detection). Can also be set later + via reader.set_graph_db(). + + Returns: + Configured MemReader instance. + """ backend = config_factory.backend if backend not in cls.backend_to_class: raise ValueError(f"Invalid backend: {backend}") reader_class = cls.backend_to_class[backend] - return reader_class(config_factory.config) + reader = reader_class(config_factory.config) + + # Set graph_db if provided (for recall operations) + if graph_db is not None: + reader.set_graph_db(graph_db) + + return reader diff --git a/src/memos/mem_reader/simple_struct.py b/src/memos/mem_reader/simple_struct.py index fa72bd063..a776d12f6 100644 --- a/src/memos/mem_reader/simple_struct.py +++ b/src/memos/mem_reader/simple_struct.py @@ -176,6 +176,9 @@ def __init__(self, config: SimpleStructMemReaderConfig): self.chat_window_max_tokens = getattr(self.config, "chat_window_max_tokens", 1024) self._count_tokens = count_tokens_text self.searcher = None + # Initialize graph_db as None, can be set later via set_graph_db for + # recall operations + self.graph_db = None def _make_memory_item( self, diff --git a/src/memos/mem_scheduler/general_modules/init_components_for_scheduler.py b/src/memos/mem_scheduler/general_modules/init_components_for_scheduler.py index 8fd60153d..3a12a9c79 100644 --- a/src/memos/mem_scheduler/general_modules/init_components_for_scheduler.py +++ b/src/memos/mem_scheduler/general_modules/init_components_for_scheduler.py @@ -305,7 +305,8 @@ def init_components() -> dict[str, Any]: ) llm = LLMFactory.from_config(llm_config) embedder = EmbedderFactory.from_config(embedder_config) - mem_reader = MemReaderFactory.from_config(mem_reader_config) + # Pass graph_db to mem_reader for recall operations (deduplication, conflict detection) + mem_reader = MemReaderFactory.from_config(mem_reader_config, graph_db=graph_db) reranker = RerankerFactory.from_config(reranker_config) feedback_reranker = RerankerFactory.from_config(feedback_reranker_config) internet_retriever = InternetRetrieverFactory.from_config( From 2c0d39520915270ad2daab7e6061e626c53716c6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B8=AD=E9=98=B3=E9=98=B3?= Date: Wed, 14 Jan 2026 20:45:02 +0800 Subject: [PATCH 2/7] feat: add merge from in mem-reader --- src/memos/graph_dbs/base.py | 2 +- src/memos/mem_reader/multi_modal_struct.py | 66 +++++++++++++++++++--- src/memos/mem_reader/simple_struct.py | 20 +++++-- src/memos/multi_mem_cube/single_cube.py | 1 + src/memos/templates/mem_reader_prompts.py | 59 +++++++++++++++++-- 5 files changed, 128 insertions(+), 20 deletions(-) diff --git a/src/memos/graph_dbs/base.py b/src/memos/graph_dbs/base.py index b76ed9d08..a8f8ff414 100644 --- a/src/memos/graph_dbs/base.py +++ b/src/memos/graph_dbs/base.py @@ -82,7 +82,7 @@ def get_node(self, id: str, include_embedding: bool = False) -> dict[str, Any] | @abstractmethod def get_nodes( - self, id: str, include_embedding: bool = False, **kwargs + self, ids: list, include_embedding: bool = False, **kwargs ) -> dict[str, Any] | None: """ Retrieve the metadata and memory of a list of nodes. diff --git a/src/memos/mem_reader/multi_modal_struct.py b/src/memos/mem_reader/multi_modal_struct.py index 3bf6d4927..0e8dd6d10 100644 --- a/src/memos/mem_reader/multi_modal_struct.py +++ b/src/memos/mem_reader/multi_modal_struct.py @@ -316,6 +316,7 @@ def _get_llm_response( custom_tags: list[str] | None = None, sources: list | None = None, prompt_type: str = "chat", + related_memories: str | None = None, ) -> dict: """ Override parent method to improve language detection by using actual text content @@ -326,6 +327,7 @@ def _get_llm_response( custom_tags: Optional custom tags sources: Optional list of SourceMessage objects to extract text content from prompt_type: Type of prompt to use ("chat" or "doc") + related_memories: related_memories in the graph Returns: LLM response dictionary @@ -360,7 +362,9 @@ def _get_llm_response( else: template = PROMPT_DICT["chat"][lang] examples = PROMPT_DICT["chat"][f"{lang}_example"] - prompt = template.replace("${conversation}", mem_str) + prompt = template.replace("${conversation}", mem_str).replace( + "${reference}", related_memories + ) custom_tags_prompt = ( PROMPT_DICT["custom_tags"][lang].replace("{custom_tags}", str(custom_tags)) @@ -418,6 +422,7 @@ def _process_string_fine( fast_memory_items: list[TextualMemoryItem], info: dict[str, Any], custom_tags: list[str] | None = None, + **kwargs, ) -> list[TextualMemoryItem]: """ Process fast mode memory items through LLM to generate fine mode memories. @@ -454,8 +459,36 @@ def _process_one_item(fast_item: TextualMemoryItem) -> list[TextualMemoryItem]: # Determine prompt type based on sources prompt_type = self._determine_prompt_type(sources) + # recall related memories + related_memories = None + memory_ids = [] + if self.graph_db: + if "user_name" in kwargs: + memory_ids = self.graph_db.search_by_embedding( + vector=self.embedder.embed(mem_str)[0], + top_k=10, + status="activated", + user_name=kwargs.get("user_name"), + filter={ + "or": [{"memory_type": "LongTermMemory"}, {"memory_type": "UserMemory"}] + }, + ) + memory_ids = set({r["id"] for r in memory_ids if r.get("id")}) + related_memories_list = self.graph_db.get_nodes( + list(memory_ids), + include_embedding=False, + user_name=kwargs.get("user_name"), + ) + related_memories = "\n".join( + ["{}: {}".format(mem["id"], mem["memory"]) for mem in related_memories_list] + ) + else: + logger.warning("user_name is null when graph_db exists") + try: - resp = self._get_llm_response(mem_str, custom_tags, sources, prompt_type) + resp = self._get_llm_response( + mem_str, custom_tags, sources, prompt_type, related_memories + ) except Exception as e: logger.error(f"[MultiModalFine] Error calling LLM: {e}") return fine_items @@ -469,6 +502,11 @@ def _process_one_item(fast_item: TextualMemoryItem) -> list[TextualMemoryItem]: .replace("长期记忆", "LongTermMemory") .replace("用户记忆", "UserMemory") ) + if "merged_from" in m: + for merged_id in m["merged_from"]: + if merged_id not in memory_ids: + logger.warning("merged id not valid!!!!!") + extra_kwargs["merged_from"] = m["merged_from"] # Create fine mode memory item (same as simple_struct) node = self._make_memory_item( value=m.get("value", ""), @@ -485,6 +523,11 @@ def _process_one_item(fast_item: TextualMemoryItem) -> list[TextualMemoryItem]: logger.error(f"[MultiModalFine] parse error: {e}") elif resp.get("value") and resp.get("key"): try: + if "merged_from" in resp: + for merged_id in resp["merged_from"]: + if merged_id not in memory_ids: + logger.warning("merged id not valid!!!!!") + extra_kwargs["merged_from"] = resp["merged_from"] # Create fine mode memory item (same as simple_struct) node = self._make_memory_item( value=resp.get("value", "").strip(), @@ -533,9 +576,7 @@ def _get_llm_tool_trajectory_response(self, mem_str: str) -> dict: return [] def _process_tool_trajectory_fine( - self, - fast_memory_items: list[TextualMemoryItem], - info: dict[str, Any], + self, fast_memory_items: list[TextualMemoryItem], info: dict[str, Any], **kwargs ) -> list[TextualMemoryItem]: """ Process tool trajectory memory items through LLM to generate fine mode memories. @@ -618,10 +659,10 @@ def _process_multi_modal_data( with ContextThreadPoolExecutor(max_workers=2) as executor: future_string = executor.submit( - self._process_string_fine, fast_memory_items, info, custom_tags + self._process_string_fine, fast_memory_items, info, custom_tags, **kwargs ) future_tool = executor.submit( - self._process_tool_trajectory_fine, fast_memory_items, info + self._process_tool_trajectory_fine, fast_memory_items, info, **kwargs ) # Collect results @@ -710,7 +751,12 @@ def get_scene_data_info(self, scene_data: list, type: str) -> list[list[Any]]: return scene_data def _read_memory( - self, messages: list[MessagesType], type: str, info: dict[str, Any], mode: str = "fine" + self, + messages: list[MessagesType], + type: str, + info: dict[str, Any], + mode: str = "fine", + **kwargs, ) -> list[list[TextualMemoryItem]]: list_scene_data_info = self.get_scene_data_info(messages, type) @@ -718,7 +764,9 @@ def _read_memory( # Process Q&A pairs concurrently with context propagation with ContextThreadPoolExecutor() as executor: futures = [ - executor.submit(self._process_multi_modal_data, scene_data_info, info, mode=mode) + executor.submit( + self._process_multi_modal_data, scene_data_info, info, mode=mode, **kwargs + ) for scene_data_info in list_scene_data_info ] for future in concurrent.futures.as_completed(futures): diff --git a/src/memos/mem_reader/simple_struct.py b/src/memos/mem_reader/simple_struct.py index a776d12f6..d97eb1b54 100644 --- a/src/memos/mem_reader/simple_struct.py +++ b/src/memos/mem_reader/simple_struct.py @@ -221,7 +221,7 @@ def _get_llm_response(self, mem_str: str, custom_tags: list[str] | None) -> dict lang = detect_lang(mem_str) template = PROMPT_DICT["chat"][lang] examples = PROMPT_DICT["chat"][f"{lang}_example"] - prompt = template.replace("${conversation}", mem_str) + prompt = template.replace("${conversation}", mem_str).replace("${reference}", "") custom_tags_prompt = ( PROMPT_DICT["custom_tags"][lang].replace("{custom_tags}", str(custom_tags)) @@ -393,7 +393,12 @@ def _process_transfer_chat_data( return chat_read_nodes def get_memory( - self, scene_data: SceneDataInput, type: str, info: dict[str, Any], mode: str = "fine" + self, + scene_data: SceneDataInput, + type: str, + info: dict[str, Any], + mode: str = "fine", + user_name: str | None = None, ) -> list[list[TextualMemoryItem]]: """ Extract and classify memory content from scene_data. @@ -412,6 +417,8 @@ def get_memory( - chunk_overlap: Overlap for small chunks (default: 50) mode: mem-reader mode, fast for quick process while fine for better understanding via calling llm + user_name: tha user_name would be inserted later into the + database, may be used in recall. Returns: list[list[TextualMemoryItem]] containing memory content with summaries as keys and original text as values Raises: @@ -435,7 +442,7 @@ def get_memory( # Backward compatibility, after coercing scene_data, we only tackle # with standard scene_data type: MessagesType standard_scene_data = coerce_scene_data(scene_data, type) - return self._read_memory(standard_scene_data, type, info, mode) + return self._read_memory(standard_scene_data, type, info, mode, user_name=user_name) def rewrite_memories( self, messages: list[dict], memory_list: list[TextualMemoryItem], user_only: bool = True @@ -561,7 +568,12 @@ def filter_hallucination_in_memories( return memory_list def _read_memory( - self, messages: list[MessagesType], type: str, info: dict[str, Any], mode: str = "fine" + self, + messages: list[MessagesType], + type: str, + info: dict[str, Any], + mode: str = "fine", + **kwargs, ) -> list[list[TextualMemoryItem]]: """ 1. raw file: diff --git a/src/memos/multi_mem_cube/single_cube.py b/src/memos/multi_mem_cube/single_cube.py index 6c3cc0cc7..0c5b4c87d 100644 --- a/src/memos/multi_mem_cube/single_cube.py +++ b/src/memos/multi_mem_cube/single_cube.py @@ -802,6 +802,7 @@ def _process_text_mem( "session_id": target_session_id, }, mode=extract_mode, + user_name=user_context.mem_cube_id, ) flattened_local = [mm for m in memories_local for mm in m] diff --git a/src/memos/templates/mem_reader_prompts.py b/src/memos/templates/mem_reader_prompts.py index 20f8150b7..134fe3956 100644 --- a/src/memos/templates/mem_reader_prompts.py +++ b/src/memos/templates/mem_reader_prompts.py @@ -143,7 +143,8 @@ "key": <字符串，唯一且简洁的记忆标题>, "memory_type": <字符串，"LongTermMemory" 或 "UserMemory">, "value": <详细、独立且无歧义的记忆陈述——若输入对话为英文，则用英文；若为中文，则用中文>, - "tags": <相关主题关键词列表（例如，["截止日期", "团队", "计划"]）> + "tags": <相关主题关键词列表（例如，["截止日期", "团队", "计划"]）>, + "merged_from": <需要被合并的参考记忆列表，当没有提供参考记忆时，不需要输出这个字段 > }, ... ], @@ -156,7 +157,7 @@ ${custom_tags_prompt} -示例： +示例1-无参考记忆： 对话： user: [2025年6月26日下午3:00]：嗨Jerry！昨天下午3点我和团队开了个会，讨论新项目。 assistant: 哦Tom！你觉得团队能在12月15日前完成吗？ @@ -183,7 +184,7 @@ "summary": "Tom目前正专注于管理一个进度紧张的新项目。在2025年6月25日的团队会议后，他意识到原定2025年12月15日的截止日期可能无法实现，因为后端会延迟。由于担心测试时间不足，他接受了Jerry提出的延期建议。Tom计划在次日早上的会议上提出将截止日期推迟至2026年1月5日。他的行为反映出对时间线的担忧，以及积极、以团队为导向的问题解决方式。" } -对话： +示例2-无参考记忆： assistant: [2025年8月15日上午10:30]: 你提到的那本《深度工作》确实很适合你现在的情况。这本书讲了......(略),作者建议每天留出2-3 小时的专注时间块，期间关闭所有通知。考虑到你下周要交的报告，可以试试早上9点到11点这个时段。 @@ -202,25 +203,71 @@ } 注意：当对话仅有助手消息时，应使用"助手推荐"、"助手建议"等表述，而非将其错误归因为用户的陈述或计划。 -另一个中文示例（注意：当用户语言为中文时，您也需输出中文）： +示例3-无参考记忆（注意：当用户语言为中文时，您也需输出中文）： { "memory list": [ { "key": "项目会议", "memory_type": "LongTermMemory", "value": "在2025年6月25日下午3点，Tom与团队开会讨论了新项目，涉及时间表，并提出了对12月15日截止日期可行性的担忧。", - "tags": ["项目", "时间表", "会议", "截止日期"] + "tags": ["项目", "时间表", "会议", "截止日期"], + "merged_from": [ + "xxxx-xxxx-xxxx-xxxx-xxx", + "xxxx-xxxx-xxxx-xxxx-xx", + ], }, ... ], "summary": "Tom 目前专注于管理一个进度紧张的新项目..." } -请始终使用与对话相同的语言进行回复。 +注意，我们可能给出部分参考记忆，这部分记忆如果和新添加的记忆大量重复，合并记忆，并在输入中多一个`merged_from`字段指明合并的记忆； +新添加的记忆如果和参考记忆有强关联，可以在提取时适当参考（但一定不要捏造记忆，十分有把握再进行参考）； +如果没有给出参考记忆、或参考记忆和新添加的记忆无关，直接忽略就好。 +示例4-带参考记忆： 对话： +user: [2026年1月13日] 冬天滑雪真的太快乐了！我打算这周末和朋友再滑一次！ +assistant：[2026年1月13日] 听起来就很棒！ +user: [2026年1月14日] 你还记得我的滑雪搭子吧？他叫Tom，我们每年都一起滑雪！这周也是！ + +参考记忆： +[xxxx-xxxx-xxxx-xxxx-01]: 用户在2025年12月29日表达了对滑雪的狂热喜爱 +[xxxx-xxxx-xxxx-xxxx-06]: 用户的滑雪搭子叫Tom +[xxxx-xxxx-xxxx-xxxx-11]: 二世谷是用户多次去过的滑雪胜地，用户在比罗夫滑雪场认识了Tom并成为好朋友 +[xxxx-xxxx-xxxx-xxxx-12]: 用户2025年1月1日和助手讨论了滑雪装备，打算新买一个滑雪背包。 + +输出： +{ + "memory list": [ + { + "key": "用户冬季滑雪计划", + "memory_type": "UserMemory", + "value": "用户在2026年1月13日计划在周末与朋友Tom再次进行滑雪活动。", + "tags": ["滑雪", "运动偏好", "计划", "冬季活动"], + }, + { + "key": "用户的滑雪伙伴叫Tom", + "memory_type": "UserMemory", + "value": "用户在2026年1月14日再次提到其滑雪搭子Tom，并进一步说明他们每年都会一起滑雪。这一描述强化了双方长期稳定的滑雪伙伴关系，在原有记忆基础上补充了新的时间规律性信息。", + "tags": ["人际关系", "滑雪搭子", "长期习惯"], + "merged_from": [ + "xxxx-xxxx-xxxx-xxxx-06", + "xxxx-xxxx-xxxx-xxxx-11", + ], + } + ], + "summary": "用户近期再次强化了自己对滑雪的热爱，并在2026年1月13日明确表示冬季滑雪带来极大的快乐，同时计划于当周周末与朋友再度滑雪。这表明滑雪对用户而言仍然是一项高度重要的活动。此外，用户在2026年1月14日补充了关于其滑雪伙伴Tom的长期关系细节，强调两人每年都会结伴滑雪，进一步巩固了此人际关系在用户生活中的重要性。" +} + +您的任务： +待提取的对话： ${conversation} +参考记忆： +${reference} + +请始终使用与对话相同的语言进行回复。 您的输出：""" SIMPLE_STRUCT_DOC_READER_PROMPT = """You are an expert text analyst for a search and retrieval system. From 75c65906333d174d0fe903dfb05df4731081c46f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B8=AD=E9=98=B3=E9=98=B3?= Date: Wed, 14 Jan 2026 21:32:36 +0800 Subject: [PATCH 3/7] feat: set merge ids archived --- src/memos/mem_reader/multi_modal_struct.py | 12 +++++++---- src/memos/multi_mem_cube/single_cube.py | 25 ++++++++++++++++++++++ 2 files changed, 33 insertions(+), 4 deletions(-) diff --git a/src/memos/mem_reader/multi_modal_struct.py b/src/memos/mem_reader/multi_modal_struct.py index 0e8dd6d10..5ae2f2489 100644 --- a/src/memos/mem_reader/multi_modal_struct.py +++ b/src/memos/mem_reader/multi_modal_struct.py @@ -466,11 +466,15 @@ def _process_one_item(fast_item: TextualMemoryItem) -> list[TextualMemoryItem]: if "user_name" in kwargs: memory_ids = self.graph_db.search_by_embedding( vector=self.embedder.embed(mem_str)[0], - top_k=10, + top_k=20, status="activated", user_name=kwargs.get("user_name"), filter={ - "or": [{"memory_type": "LongTermMemory"}, {"memory_type": "UserMemory"}] + "or": [ + {"memory_type": "LongTermMemory"}, + {"memory_type": "UserMemory"}, + {"memory_type": "WorkingMemory"}, + ] }, ) memory_ids = set({r["id"] for r in memory_ids if r.get("id")}) @@ -506,7 +510,7 @@ def _process_one_item(fast_item: TextualMemoryItem) -> list[TextualMemoryItem]: for merged_id in m["merged_from"]: if merged_id not in memory_ids: logger.warning("merged id not valid!!!!!") - extra_kwargs["merged_from"] = m["merged_from"] + info_per_item["merged_from"] = m["merged_from"] # Create fine mode memory item (same as simple_struct) node = self._make_memory_item( value=m.get("value", ""), @@ -527,7 +531,7 @@ def _process_one_item(fast_item: TextualMemoryItem) -> list[TextualMemoryItem]: for merged_id in resp["merged_from"]: if merged_id not in memory_ids: logger.warning("merged id not valid!!!!!") - extra_kwargs["merged_from"] = resp["merged_from"] + info_per_item["merged_from"] = resp["merged_from"] # Create fine mode memory item (same as simple_struct) node = self._make_memory_item( value=resp.get("value", "").strip(), diff --git a/src/memos/multi_mem_cube/single_cube.py b/src/memos/multi_mem_cube/single_cube.py index 0c5b4c87d..6aea6997f 100644 --- a/src/memos/multi_mem_cube/single_cube.py +++ b/src/memos/multi_mem_cube/single_cube.py @@ -832,6 +832,31 @@ def _process_text_mem( sync_mode=sync_mode, ) + # Mark merged_from memories as archived when provided in add_req.info + for memory in flattened_local: + merged_from = (memory.metadata.info or {}).get("merged_from") + if merged_from: + old_ids = ( + merged_from if isinstance(merged_from, (list | tuple | set)) else [merged_from] + ) + if self.mem_reader and self.mem_reader.graph_db: + for old_id in old_ids: + try: + self.mem_reader.graph_db.update_node( + str(old_id), {"status": "archived"} + ) + self.logger.info( + f"[SingleCubeView] Archived merged_from memory: {old_id}" + ) + except Exception as e: + self.logger.warning( + f"[SingleCubeView] Failed to archive merged_from memory {old_id}: {e}" + ) + else: + self.logger.warning( + "[SingleCubeView] merged_from provided but graph_db is unavailable; skip archiving." + ) + text_memories = [ { "memory": memory.memory, From 6e80154780c471148ec4157f208fad2fb15fe331 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B8=AD=E9=98=B3=E9=98=B3?= Date: Wed, 14 Jan 2026 21:43:25 +0800 Subject: [PATCH 4/7] feat: update en mem-reader prompt --- src/memos/templates/mem_reader_prompts.py | 56 ++++++++++++++++++++--- 1 file changed, 50 insertions(+), 6 deletions(-) diff --git a/src/memos/templates/mem_reader_prompts.py b/src/memos/templates/mem_reader_prompts.py index 134fe3956..f2d15cfb8 100644 --- a/src/memos/templates/mem_reader_prompts.py +++ b/src/memos/templates/mem_reader_prompts.py @@ -28,7 +28,8 @@ "key": , "memory_type": , "value": , - "tags": + "tags": , + "merged_from": }, ... ], @@ -41,7 +42,7 @@ ${custom_tags_prompt} -Example: +Example 1 — No reference memories: Conversation: user: [June 26, 2025 at 3:00 PM]: Hi Jerry! Yesterday at 3 PM I had a meeting with my team about the new project. assistant: Oh Tom! Do you think the team can finish by December 15? @@ -69,7 +70,7 @@ "summary": "Tom is currently focused on managing a new project with a tight schedule. After a team meeting on June 25, 2025, he realized the original deadline of December 15 might not be feasible due to backend delays. Concerned about insufficient testing time, he welcomed Jerry’s suggestion of proposing an extension. Tom plans to raise the idea of shifting the deadline to January 5, 2026 in the next morning’s meeting. His actions reflect both stress about timelines and a proactive, team-oriented problem-solving approach." } -Dialogue: +Example 2 — No reference memories: assistant: [10:30 AM, August 15, 2025]: The book Deep Work you mentioned is indeed very suitable for your current situation. The book explains … (omitted). The author suggests setting aside 2–3 hours of focused work blocks each day and turning off all notifications during that time. Considering that you need to submit a report next week, you could try using the 9:00–11:00 AM time slot for focused work. @@ -89,7 +90,7 @@ Note: When the dialogue contains only assistant messages, phrasing such as “assistant recommended” or “assistant suggested” should be used, rather than incorrectly attributing the content to the user’s statements or plans. -Another Example in Chinese (注意: 当user的语言为中文时，你就需要也输出中文)： +Example 3 — No reference memories (note: if the user’s language is Chinese, output must also be Chinese): { "memory list": [ { @@ -103,11 +104,54 @@ "summary": "Tom 目前专注于管理一个进度紧张的新项目..." } -Always respond in the same language as the conversation. +Note: We may provide partial reference memories. If newly extracted memories substantially overlap with reference memories, merge them and include a `merged_from` field indicating the merged memory IDs. +If newly extracted memories are strongly related to reference memories, you may appropriately reference them during extraction (but never fabricate memories — only reference them when you are very confident). +If no reference memories are provided, or if they are unrelated to the new memories, simply ignore them. -Conversation: +Example 4 — With reference memories: +Dialogue: +user: [January 13, 2026] Winter skiing is so much fun! I’m planning to go skiing again with friends this weekend! +assistant: [January 13, 2026] That sounds great! +user: [January 14, 2026] You remember my ski buddy, right? His name is Tom. We ski together every year — including this week! + +Reference memories: +[xxxx-xxxx-xxxx-xxxx-01]: The user expressed a strong passion for skiing on December 29, 2025 +[xxxx-xxxx-xxxx-xxxx-06]: The user’s ski buddy is named Tom +[xxxx-xxxx-xxxx-xxxx-11]: Niseko is a ski destination the user has visited multiple times; the user met Tom at Hirafu Ski Resort and became close friends +[xxxx-xxxx-xxxx-xxxx-12]: On January 1, 2025, the user discussed skiing equipment with the assistant and planned to buy a new ski backpack + +Output: +{ + "memory list": [ + { + "key": "User's winter skiing plan", + "memory_type": "UserMemory", + "value": "On January 13, 2026, the user planned to go skiing again over the weekend with their friend Tom.", + "tags": ["skiing", "sports preference", "plan", "winter activity"] + }, + { + "key": "User's ski partner is named Tom", + "memory_type": "UserMemory", + "value": "On January 14, 2026, the user again mentioned their ski partner Tom and further explained that they ski together every year. This statement reinforces their long-term and stable skiing partnership and adds new information about its regular annual pattern.", + "tags": ["interpersonal relationship", "ski partner", "long-term habit"], + "merged_from": [ + "xxxx-xxxx-xxxx-xxxx-06", + "xxxx-xxxx-xxxx-xxxx-11" + ] + } + ], + "summary": "The user recently reinforced their strong passion for skiing and, on January 13, 2026, explicitly stated that winter skiing brings them great joy and that they planned to ski again with a friend over the weekend. This indicates that skiing remains a highly significant activity in the user’s life. Additionally, on January 14, 2026, the user elaborated on their long-term relationship with their ski partner Tom, emphasizing that they ski together every year. This further solidifies the importance of this interpersonal relationship in the user’s personal experiences." +} + +Your task: +Dialogue to be extracted: ${conversation} +Reference memories: +${reference} + +Always respond in the same language as the conversation. + Your Output:""" SIMPLE_STRUCT_MEM_READER_PROMPT_ZH = """您是记忆提取专家。 From c3991dc237e1a1445d0a25d50c169add31b6c2e4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B8=AD=E9=98=B3=E9=98=B3?= Date: Wed, 14 Jan 2026 21:59:11 +0800 Subject: [PATCH 5/7] fix: abstract --- src/memos/mem_reader/base.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/memos/mem_reader/base.py b/src/memos/mem_reader/base.py index b34abf9a1..c150051df 100644 --- a/src/memos/mem_reader/base.py +++ b/src/memos/mem_reader/base.py @@ -20,6 +20,7 @@ class BaseMemReader(ABC): def __init__(self, config: BaseMemReaderConfig): """Initialize the MemReader with the given configuration.""" + @abstractmethod def set_graph_db(self, graph_db: "BaseGraphDB | None") -> None: """ Set the graph database instance for recall operations. From 4f30e4458fdb38ed57e0355fea2669bbdad2de43 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B8=AD=E9=98=B3=E9=98=B3?= Date: Wed, 14 Jan 2026 22:08:34 +0800 Subject: [PATCH 6/7] fix: set graph db bug --- src/memos/mem_reader/base.py | 1 - src/memos/mem_reader/simple_struct.py | 9 ++++++++- 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/src/memos/mem_reader/base.py b/src/memos/mem_reader/base.py index c150051df..87bf43b0f 100644 --- a/src/memos/mem_reader/base.py +++ b/src/memos/mem_reader/base.py @@ -32,7 +32,6 @@ def set_graph_db(self, graph_db: "BaseGraphDB | None") -> None: Args: graph_db: The graph database instance, or None to disable recall operations. """ - self.graph_db = graph_db @abstractmethod def get_memory( diff --git a/src/memos/mem_reader/simple_struct.py b/src/memos/mem_reader/simple_struct.py index d97eb1b54..6f4542c7a 100644 --- a/src/memos/mem_reader/simple_struct.py +++ b/src/memos/mem_reader/simple_struct.py @@ -5,7 +5,7 @@ import traceback from abc import ABC -from typing import Any, TypeAlias +from typing import TYPE_CHECKING, Any, TypeAlias from tqdm import tqdm @@ -16,6 +16,10 @@ from memos.embedders.factory import EmbedderFactory from memos.llms.factory import LLMFactory from memos.mem_reader.base import BaseMemReader + + +if TYPE_CHECKING: + from memos.graph_dbs.base import BaseGraphDB from memos.mem_reader.read_multi_modal import coerce_scene_data, detect_lang from memos.mem_reader.utils import ( count_tokens_text, @@ -180,6 +184,9 @@ def __init__(self, config: SimpleStructMemReaderConfig): # recall operations self.graph_db = None + def set_graph_db(self, graph_db: "BaseGraphDB | None") -> None: + self.graph_db = graph_db + def _make_memory_item( self, value: str, From c4ecfc804b41cdd6b1dd5868c7fb565be1049f55 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B8=AD=E9=98=B3=E9=98=B3?= Date: Thu, 15 Jan 2026 11:37:20 +0800 Subject: [PATCH 7/7] fix: prompt build bug: replace None --- src/memos/mem_reader/multi_modal_struct.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/memos/mem_reader/multi_modal_struct.py b/src/memos/mem_reader/multi_modal_struct.py index 5ae2f2489..a9b108f15 100644 --- a/src/memos/mem_reader/multi_modal_struct.py +++ b/src/memos/mem_reader/multi_modal_struct.py @@ -362,8 +362,9 @@ def _get_llm_response( else: template = PROMPT_DICT["chat"][lang] examples = PROMPT_DICT["chat"][f"{lang}_example"] + related_memories_str = related_memories if related_memories is not None else "" prompt = template.replace("${conversation}", mem_str).replace( - "${reference}", related_memories + "${reference}", related_memories_str ) custom_tags_prompt = (